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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
A new general biomarker-based incidence estimator
Epidemiology, Volume 23, No. 5, Year 2012
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Description
BACKGROUND:: Estimating disease incidence from cross-sectional surveys, using biomarkers for "recent" infection, has attracted much interest. Despite widespread applications to HIV, there is currently no consensus on the correct handling of biomarker results classifying persons as "recently" infected long after the infections occurred. METHODS:: We derive a general expression for a weighted average of recent incidence that-unlike previous estimators-requires no particular assumption about recent infection biomarker dynamics or about the demographic and epidemiologic context. This is possible through the introduction of an explicit timescale T that truncates the period of averaging implied by the estimator. RESULTS:: The recent infection test dynamics can be summarized into 2 parameters, similar to those appearing in previous estimators: a mean duration of recent infection and a false-recent rate. We identify a number of dimensionless parameters that capture the bias that arises from working with tractable forms of the resulting estimator and elucidate the utility of the incidence estimator in terms of the performance of the recency test and the population state. Estimation of test characteristics and incidence is demonstrated using simulated data. The observed confidence interval coverage of the test characteristics and incidence is within 1% of intended coverage. CONCLUSIONS:: Biomarker-based incidence estimation can be consistently adapted to a general context without the strong assumptions of previous work about biomarker dynamics and epidemiologic and demographic history. © 2012 by Lippincott Williams & Wilkins.
Authors & Co-Authors
Kassanjee, Reshma
South Africa, Stellenbosch
Stellenbosch University
South Africa, Johannesburg
University of the Witwatersrand
McWalter, Thomas Andrew
South Africa, Stellenbosch
Stellenbosch University
South Africa, Johannesburg
University of the Witwatersrand
Bärnighausen, Till Winfried
United States, Boston
Harvard T.h. Chan School of Public Health
South Africa, Durban
University of Kwazulu-natal
Welte, Alex
South Africa, Stellenbosch
Stellenbosch University
Statistics
Citations: 94
Authors: 4
Affiliations: 4
Identifiers
Doi:
10.1097/EDE.0b013e3182576c07
ISSN:
10443983
e-ISSN:
15315487
Research Areas
Health System And Policy
Infectious Diseases
Study Design
Cross Sectional Study
Cohort Study